Hybrid ML/Data Engineer for Health AI Pipelines

UCSF Health, AG; San Francisco (CA); Hybride; USD 140 000 - 190 000; Plein temps

Résumé du poste

UCSF is seeking a Machine Learning and Data Engineer to lead data pipelines and infrastructure for deploying ML/AI tools within the AER team. The role emphasizes collaboration with UCSF technical teams and productionizing models in HIPAC infrastructure.

Ideal candidates have 6+ years in AI/ML engineering, strong Python/SQL, and cloud experience. Epic Clarity/Caboodle knowledge is a plus; flexibility includes on-site meetings and lab collaboration.

Qualifications

• Bachelor's degree or equivalent experience in CS/EE or related field.
• 6+ years designing and maintaining AI/ML applications with increasing responsibility.
• Experience with data analysis and ML tools such as Jupyter, Pandas, scikit-learn, NumPy/Scipy, PyTorch.
• Strong Python and SQL skills; production-grade code and scale-focused mindset.
• Experience deploying and monitoring AI/ML models and pipelines; MLOps/CI-CD familiarity.
• Knowledge of cloud platforms (AWS, GCP, Azure) and data warehousing concepts.
• Familiarity with Epic data structures (Clarity/Caboodle) preferred.

Responsabilités

• Lead development, implementation, and maintenance of data pipelines for ML/AI deployments.
• Collaborate with UCSF teams to productionize AI/ML tools within HIPAC and AER.
• Design metrics to monitor AI/ML tools deployed in UCSF Health environments.
• Communicate technical concepts to both technical and non-technical stakeholders.

Connaissances

Python

SQL

ML pipelines

CI/CD

MLOps

Epic Clarity

Cloud platforms

Data warehousing

Communication

Teamwork

Formation

Bachelor's degree or equivalent experience

Outils

Jupyter

Pandas

scikit-learn

NumPy

PyTorch

Description du poste

UCSF is seeking a Machine Learning and Data Engineer to lead data pipelines and infrastructure for deploying ML/AI tools within the AER team. The role emphasizes collaboration with UCSF technical teams and productionizing models in HIPAC infrastructure.

Ideal candidates have 6+ years in AI/ML engineering, strong Python/SQL, and cloud experience. Epic Clarity/Caboodle knowledge is a plus; flexibility includes on-site meetings and lab collaboration.